Sentence Similarity
sentence-transformers
Safetensors
French
bidirectional_pplx_qwen3
trimmed
custom_code
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use alphaedge-ai/pplx-embed-v1-fra-32768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use alphaedge-ai/pplx-embed-v1-fra-32768 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("alphaedge-ai/pplx-embed-v1-fra-32768", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "PPLXQwen3Model" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration.PPLXQwen3Config", | |
| "AutoModel": "modeling.PPLXQwen3Model" | |
| }, | |
| "eos_token_id": 32752, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 1024, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "layer_types": [ | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention" | |
| ], | |
| "max_position_embeddings": 32768, | |
| "max_window_layers": 28, | |
| "model_type": "bidirectional_pplx_qwen3", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 28, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 32752, | |
| "rms_norm_eps": 1e-06, | |
| "sliding_window": null, | |
| "tie_word_embeddings": true, | |
| "transformers.js_config": { | |
| "use_external_data_format": { | |
| "model.onnx": 2, | |
| "model_q4.onnx": 1, | |
| "model_quantized.onnx": 1 | |
| } | |
| }, | |
| "transformers_version": "5.3.0.dev0", | |
| "use_bidirectional_attention": true, | |
| "use_cache": false, | |
| "use_sliding_window": false, | |
| "vocab_size": 32768, | |
| "rope_theta": 1000000, | |
| "torch_dtype": "bfloat16" | |
| } |